Deeplearning4j

Eclipse Deeplearning4j is an open source, distributed deep learning framework for the Java Virtual Machine. It gives Java and Scala teams a complete ecosystem for building, training and deploying neural networks, with native GPU acceleration through CUDA and high performance CPU computation through OpenBLAS and oneDNN. The documentation site is hosted by Konduit and covers the full stack. It suits enterprises and engineers who want machine learning inside existing JVM applications instead of a separate Python service. The ecosystem is split into focused libraries: ND4J for n dimensional arrays, often described as NumPy for Java; Deeplearning4j for neural network training and inference; SameDiff for automatic differentiation and graph execution; DataVec for data loading, transformation and ETL; and Python4J with a NumPy bridge. Model import covers Keras, TensorFlow, ONNX Runtime, Apache TVM and GGML and GGUF files, and newer sections document an LLM and VLM stack plus parameter efficient fine tuning and reinforcement learning alignment training. Supporting material includes distributed training, a model zoo, a training UI, the OmniHub model catalogue, the Arbiter hyperparameter tuning tool, and setup guides for Maven, Gradle, SBT, cuDNN and memory workspaces. Deeplearning4j is free, open source software under the Eclipse Foundation. The documentation site publishes no pricing and no paid tier. The release notes list a series of milestone builds and a separate rewrite line, so teams should check which release the documentation they are reading applies to before starting a project.